Towards the Future Generation of Railway Localization Exploiting RTK and GNSS

This repository contains the datasets acquired by ETH-PBL in conjunction with Unibo and SADEL during two days of testing in October 2022 near Modena, Italy. The data were acquired using two sensor nodes developed by ETH Zurich running a STM32L452CEU6 MCU. Each node collected data on the motion of the train using an ST ASM330LHH automotive grade IMU as well as a u-blox ZED-F9P GNSS module fed with live RTCM-data from a closeby RTK base station provided by SADEL. The base station utilized another ZED-F9P GNSS module connected to a Raspberry Pi which transmitted the generated RTCM correction packages over a raw TCP socket. The data was then received using a u-blox SARA-R4 cellular network module. The track was chosen as it exposes a variety of interesting GNSS environments. Encountered environments are ranging from urban over suburban to open field environments as well as one tunnel. Due to this composition, the availability of cellular connection and thus RTK correction data was patchy but mostly stable. The two sensor nodes were fixed to the Train Chassis, one centered in the train and the other positioned on the left side in driving orientation. Node 1 was placed on the floor in front of the driver's seat and positioned to be aligned with the center of the train in the lateral direction. A TOPGNSS TOP106 L1/L2 multi-band antenna was placed below the rear-facing windscreen also aligned with the same axis. Node 2 was mounted on a window on the left side of the train when facing in the direction of travel. This is approximately 1m above the floor and 1.4m left to the lateral center of the train. An ANN-MB00 L1/L2 antenna was attached to the outside frame of the train above the window. This dataset is linked with the GitHub repository at Railway-Precise-Localization where the data format description and the pre-processing scripts are provided.

本仓库收录了ETH-PBL联合博洛尼亚大学（Unibo）与SADEL，于2022年10月在意大利摩德纳附近开展的为期两天的测试所采集的数据集。本次采集的数据由苏黎世联邦理工学院（ETH Zurich）研发的两款传感器节点完成，节点搭载STM32L452CEU6微控制单元（Microcontroller Unit, 简称MCU）。每个传感器节点采用意法半导体（ST）ASM330LHH车规级惯性测量单元（Inertial Measurement Unit, 简称IMU），以及u-blox ZED-F9P全球导航卫星系统（Global Navigation Satellite System, 简称GNSS）模块采集列车运动数据；该GNSS模块接收由SADEL提供的邻近RTK基准站发送的实时RTCM差分修正数据。该基准站搭载另一台ZED-F9P GNSS模块，并连接至树莓派（Raspberry Pi），树莓派通过原始TCP套接字发送生成的RTCM修正数据包。后续数据通过u-blox SARA-R4蜂窝网络模块完成接收。本次测试选取的线路涵盖了多种典型GNSS信号传播场景，包括城市、郊区、开阔田野环境以及一处隧道。受线路场景分布影响，蜂窝网络连接及配套的RTK修正数据可用性存在波动，但整体保持稳定。两款传感器节点均固定于列车底盘：一台布置于列车纵向中心线上，另一台沿行驶方向布置于列车左侧。1号节点安装于驾驶员座椅前方的地板处，横向与列车中心线对齐；其配套的TOPGNSS TOP106 L1/L2多频段天线布置于后挡风玻璃下方，同样与列车中心线对齐。2号节点安装于列车行驶方向左侧的车窗处，安装高度距地板约1米，横向距列车中心线左侧1.4米；其配套的ANN-MB00 L1/L2天线固定于车窗上方的列车外部框架上。本数据集关联至GitHub上的Railway-Precise-Localization仓库，该仓库提供了数据格式说明与预处理脚本。